What if we turned the sci-fi economics wiki into data?

EarthOS Scifi Economics
1

Recently I have been adding new material to the Science Fiction Economics wiki here on Edgeryders. It’s becoming quite large and sprawling: at 5,000 words it is already at the point when it needs to become more hypertextual and navigable, at the very least.

But here is the thing: I have the impression that, as it gets bigger, this thing wants to be turned into data. And maybe, given my own academic work, I have a hammer, so i see everything as nails: but I would love to grow this thing a bit more and then look at the network of co-occurring economic concepts and ideas in science fiction. The idea is just another angle on a familiar concept in network science: when you have a bunch of document all tagged with keywords, you can easily induce a network of the keywords.

  • The network is undirected and weighted.
  • Two keywords are connected by an edge of weight equal to the number of documents in which they bot appear.

The logic here is exactly the same. Keywords are economic concepts; documents are science fiction novels or short stories. For example, irredeemable personal debt figures both in Doctorow’s Walkaway and in Karl Schroeder’s Stealing Worlds. Walkaway (but not Worlds) also has commons-based peer production, and Worlds (but not Walkaway) has smart contracts. Even if we stop here, we have a small network, with takes the shape of a V with irredeemable personal debt at center, linked to both commons-based peer production and smart contracts. Where it starts to get interesting is if we start to see consensus: if, in other words, the same clusters of economic concepts keep reappearing across different works and authors.

What might such a network tell us exactly? At the simplest level, it would give us a map of what, in economic thinking, appeals to the imagination. Squinting at it, an anthropologist might be able to say something about the values, aspirations, and fears around the economy of science fiction authors and, indirectly, readers. It’s at the border between STS and humanities analytics.

Many ways to do it, of course. A fairly unwieldy (but machine-friendly) way is to use our own forum here plus the OpenEthnographer tool: the wiki’s text would become a set of one-post topics, each one dedicated to a specific author. I could then add the keywords with Open Ethnographers and BANG! The network is there.

Any thoughts, anyone? @Kyle ? @petussing? @Nica ? @zazizoma ? @nadia ? Others?

1 Like
2

Okay, first off I love the idea. I’ve been working on mindmapping some complexity economics topics, which isn’t quite the same as demonstrating multiple linkages between concepts, but it does embed a particular concept with others.
Second, and we’ve had this conversation before, our illustrious SF writers are missing a cohesive economic theory that provides the pathway from the imaginative world to the real world. To use your example, Stealing Worlds talks about smart contracts but not at all about actual production. Where does that food that speaks to the delivery person about where it wants to go come from? I think Schroeder took a shortcut by placing most of his narrative in a virtual world where things don’t actually need to be procured and manufactured. Doctorow get’s a little closer with fab technology, but nothing about supply chains and distribution.
That said, perhaps the networks could be structured to illuminate the missing nodes?
Best!

1 Like
3

This is for sure. Though it’s not entirely fair to fault a sci-fi author for going speculative!

4

Definitely!

5

We’re ALL missing that theory ; )

6

Alberto-

If I understand these concepts aright, it seems to me that you are thinking of how to organize the data that we have currently, so that ideas, especially those that connect to other ideas, don’t get lost. That seems worthwhile. Try it and see if it works on the small, controllable scale you have, and if so, expand.

Zazizoma’s idea seems to me to be to fill in the blanks and connect the dots – like Tolkien’s Silmarillion, the backstory for his entire universe – only for the economics instead of the mythology. If done from an objective point of view, this may have the benefit of identifying what works and separating it from what does not. But the problem is that like the Utopian sci-fi of the late 19th century, authors fall into justifying the system that they have to the extent that they refuse to countenance anything that might imply that it won’t work with real people. So what seems like “connecting dots” might simply be yet one more strenuous fantasy attempt at self-justification.

Ultimately the only way to avoid that is a full-blown plunge into practice. That is what I earlier pointed out is what did NOT happen for Proudhon’s Mutualism, which has meant that from that day to this it has not been seriously tried on a large scale. Current experiments with Universal Basic Income are interesting in that respect, but in fact they can’t tell us much, as they are neither universal nor long-term, and so they only tell us the effects of poor people in a specific cultural milieu getting a guaranteed income for a modest period. By the way, for a science fiction treatment of this theme, look at Robert Heinlein’s 1938 book “For Us, the Living”, published posthumously. It is an important and overlooked work.

It is not impossible that a sufficiently detailed computer simulation could address some of this, but it would need to be programmed with the latest data in social psychology, and as you are aware, we recently found out that some 40% of basic “accepted” studies in psychology cannot be replicated… So it is early days for that – where is Hari Seldon when you need him…?

2 Likes
7

Wow, I definitely will. It’s always Heinlein.

@zazizoma is an ABM modeller, and any sufficiently advanced ABM is indistinguishable from psychohistory! :sweat_smile:

(A joke, everyone! Only a joke! No need for those pitchforks!)

8

I really like the idea of this kind of data!

It would be really nice for readers to be able to choose books based on the connection of economic concepts. It may be a niche market, but I know I’d pick out a new read of it connected concepts together in ways I’ve never thought of.

I also think the data visualization would be really cool to see. Seeing what economic concepts we currently link together may help showcase the unexplored and missing elements in a way that could inspire writers to address. Perhaps that is similar to what @zazizoma had in mind?

So what are the immediate steps in making that happen? Would more people adding to the wiki be helpful?

9

The first thing to do is to decide in what form to re-encode the data. The one I proposed has many advantages, and I am inclined to go with it, but any counterproposal would be welcome. The second is…

… this, indeed, because these networks risk being very sparse (depending on how hard we consolidate our taxonomy of economic terms). So, more data => a more connected, therefore more meaningful, network.

1 Like
10

Alberto-

Do you know these people? They are in Europe and seem like they might be good contacts for you.

1 Like
11

Nice to read you Philip! No, I was not aware of BIEN in particular. Good to have them on the radar, thank you!

1 Like
12

Ping @yudhanjaya!

13

Many moons later, somehow, the stars aligned, and it came to pass that @yudhanjaya came to visit us in Brussels. It was really wonderful to finally meet in person! And, as a very welcome side effect of that encounter, we ended up revisiting my old project of turning our Sci-Fi Economics wiki into some kind of structured data.

This is supposed to be the age of Artificial Intelligence, and for once entity extraction is actually a good use case of modern-day Large Language Models. So, Yudha cooked up almost on the fly an entity extractor that reads reviews of science fiction books, extracts economic concepts from them and arranges it in a JSON file. The magic of entity extraction is farmed out to an appropriately prompted LLM; the entire thing is packaged into a Python script that calls the LLM’s APIs.

The main problem with all that is to get the granularity of the concepts right. For example, “economics” is not granular enough – it contains too much stuff that we want to resolve into more operational concepts. On the opposite side, “market mechanisms” is probably too granular, especially if “markets” is also present, since these two expressions have the same meaning in economics discourse. So I did some tweaking to the code and fed it the economic analysis of 25 sci-fi works (mostly novels) that had been posted on this forum over the years.

Click here to see the entire list of titles and their authors 
2312, by Kim Stanley Robinson

A Half-Built Garden, by Ruthanna Emrys

Another Now, by Yanis Varoufakis

Autonomous, by Annalee Newitz

Distraction, by Bruce Sterling

Freedom TM, by Daniel Suarez

Gamechanger, by L. X. Beckett

Makers, by Cory Doctorow

MetaGame, by Sam Landstrom

New York 2140, by Kim Stanley Robinson

Numbercaste, by Yudhanjaya Wijeratne

Our Shared Storm: A Movel of Five Climate Futures, by Andrew Dana Hudson

Red Plenty, by Francis Spufford

Scholomance Trilogy, by Naomi Novik

Stealing Worlds, by Karl Schroeder

The Caryatids, by Bruce Sterling

The Culture Series, by Iain Banks

The Dispossessed, by Ursula Le Guin

The Lost Cause, by Cory Doctorow

The Ministry for the Future, by Kim Stanley Robinson

The Moon is a Harsh Mistress, by Robert A. Heinlein

The Terraformers, by Annalee Newitz

Utopia Five, by A. E. Currie

Walkaway, by Cory Doctorow

Webs of Varok, by Cary Neeper

I ended up with 140 economic concepts associated to the books; I then narrowed them down to 135, by merging some that were very close (for example Creative Destruction and Disruptive Innovation). Next, because everyone loves a graph, I used Tulip to induce a 2-mode network where books connect to economic concepts. Books are represented as green nodes, economic concepts as blue nodes.

Since some economic concepts feature in more than one book, the network is a small world network, where most of the nodes are connected to one another.

image
image1200×965 170 KB

What does this tell us? As a macro property, not much. The fictional economies in 22 of my 25 books appear to share some features, with only three of them forming "islands of concepts to the north of the graph. The action – if there is any to be had – is going to be local, with economic institutions and concepts gluing together pieces of work from different authors describing different worlds. Community detection analysis might reveal “families” of economic concepts that are not obvious to scholars – a contribution of sci-fi authors as a group to economic analysis. Another approach would be to extract not generic “economic concepts”, but some more homogenous – hence tractable – aggregate: for example, economic policies (like Job Guarantee), or indicators (like Social credit scoring).

There is also something to be said for looking at methods for extraction other than LLMs – for example ethnographic coding. There are some puzzling phenomena in the data: why did the bot extract Social credit scoring from Karl Schroeder’s Stealing Worlds and Sam Langstrom’s Metagame, but not from Yudha’s own Numbercaste? Yes, Yudha frames his number more in terms of reputation, but it is a score, and it maps to social credit, and it is the entire point of the novel. I could redo the coding manually, or just edit that done by the bot – in this case I could merge Social credit scoring with Algorithmic reputation system – this would connect Numbercaste and the economic concepts therein to the graph’s giant component.

Anyway, this is obviously a sort of “hello world”, rather than a piece of research. Grateful for ideas on how to improve it, especially from @zazizoma, @petussing, @yudhanjaya, @Nica… The Gihub repo is here, including graphs and input files.